25 citations · 28 across the 11 of their papers we have counts for
4 papers · 1 filter
How Well Can General Vision-Language Models Learn Medicine By Watching Public Educational Videos?
Rahul Thapa, Andrew Li, Qingyang Wu +8
Publicly available biomedical videos, such as those on YouTube, serve as valuable educational resources for medical students. Unlike standard machine learning datasets, these video…
SMIR: Efficient Synthetic Data Pipeline To Improve Multi-Image Reasoning
Andrew Li, Rahul Thapa, Rahul Chalamala +3
Vision-Language Models (VLMs) excel at understanding single images, aided by high-quality instruction datasets. However, multi-image reasoning remains underexplored in the open-sou…
Locality Alignment Improves Vision-Language Models
Ian Covert, Tony Sun, James Zou +1
Vision language models (VLMs) have seen growing adoption in recent years, but many still struggle with basic spatial reasoning errors. We hypothesize that this is due to VLMs adopt…
Dragonfly: Multi-Resolution Zoom-In Encoding Enhances Vision-Language Models
Rahul Thapa, Kezhen Chen, Ian Covert +4
Recent advances in vision-language models (VLMs) have demonstrated the advantages of processing images at higher resolutions and utilizing multi-crop features to preserve native re…